The books "Linked: The New Science of Networks" by Albert-László Barabási and "Six Degrees: The Science of a Connected Age" by Duncan J. Watts explore the science of networks, showing how various networks—such as social, business, and biological—follow similar patterns and rules. Barabási's book discusses the concept of "six degrees of separation," which originated from a social experiment by Stanley Milgram. Watts's book provides a more mathematical perspective, focusing on network models and their applications. The concept of network structures was first introduced by Erdős and Renyi in the 1950s with the G(n,p) model. Later, Watts and Strogatz developed the small-world model, which combines short path lengths with high clustering. This model was later refined by Barabási and Albert, who introduced the preferential attachment model, which explains the power-law distribution of node degrees in many real-world networks. The preferential attachment model has been applied to various systems, including social networks, metabolic networks, and the World Wide Web. However, the model has limitations, such as the potential for extreme cases where one node connects to all others. The power-law distribution of node degrees has significant implications for network behavior, such as the spread of diseases and the resilience of networks to random failures. Both books are informative and engaging, though Barabási's book is more accessible to a general audience, while Watts's book is more technical. The books highlight the importance of understanding network structures in various fields, from science to business. However, they do not delve deeply into the mathematical details behind the models, which are covered in more detailed works like Mark Newman's article.The books "Linked: The New Science of Networks" by Albert-László Barabási and "Six Degrees: The Science of a Connected Age" by Duncan J. Watts explore the science of networks, showing how various networks—such as social, business, and biological—follow similar patterns and rules. Barabási's book discusses the concept of "six degrees of separation," which originated from a social experiment by Stanley Milgram. Watts's book provides a more mathematical perspective, focusing on network models and their applications. The concept of network structures was first introduced by Erdős and Renyi in the 1950s with the G(n,p) model. Later, Watts and Strogatz developed the small-world model, which combines short path lengths with high clustering. This model was later refined by Barabási and Albert, who introduced the preferential attachment model, which explains the power-law distribution of node degrees in many real-world networks. The preferential attachment model has been applied to various systems, including social networks, metabolic networks, and the World Wide Web. However, the model has limitations, such as the potential for extreme cases where one node connects to all others. The power-law distribution of node degrees has significant implications for network behavior, such as the spread of diseases and the resilience of networks to random failures. Both books are informative and engaging, though Barabási's book is more accessible to a general audience, while Watts's book is more technical. The books highlight the importance of understanding network structures in various fields, from science to business. However, they do not delve deeply into the mathematical details behind the models, which are covered in more detailed works like Mark Newman's article.